Senior AWS Python Data Engineer

Cloud Hybrid Technologies, LLC; Houston (TX); On-site; USD 100,000 - 140,000; Full time

Job summary

A technology firm in Houston is seeking an experienced backend developer to collaborate on building scalable ML and data systems. The role requires over 5 years of experience in Python and a strong background in optimizing large-scale data pipelines. Responsibilities include the development of machine learning infrastructure and implementing cloud-native architectures using AWS services. Candidates should possess solid software engineering principles and experience with Infrastructure as Code tools like CloudFormation or Terraform. This position offers an opportunity to work in a dynamic environment focused on cutting-edge technologies.

Qualifications

• 5+ years of professional experience developing backend systems using Python.
• Experience deploying machine learning models and managing ML workflows in production.
• Solid understanding of software engineering principles, including design patterns and version control.

Responsibilities

• Collaborate with Data Scientists and Platform Engineers to build scalable ML and data systems.
• Develop and maintain high-performance data pipelines and machine learning infrastructure.
• Implement Infrastructure as Code (IaC) using CloudFormation, Terraform, or AWS CDK.

Skills

Python

Cloud engineering on AWS

Machine learning operations (MLOps)

CI/CD

RESTful APIs

Tools

AWS CDK

CloudFormation

Terraform

Neo4j

Job description

Responsibilities

• Collaborate with Data Scientists and Platform Engineers to build scalable ML and data systems
• Develop and maintain high-performance, distributed data pipelines and machine learning infrastructure
• Convert machine learning models into production-ready services and APIs
• Automate model training, validation, deployment, and inferencing pipelines
• Design fault-tolerant, secure, and cost-effective cloud-native architectures using AWS services
• Implement Infrastructure as Code (IaC) using CloudFormation, Terraform, or AWS CDK
• Build CI/CD pipelines for deployment and testing automation
• Establish software engineering best practices including modularity, reusability, test coverage, and documentation

Requirements

• 5+ years of professional experience developing backend systems using Python
• Strong background in building and optimizing large-scale data pipelines and distributed systems
• Experience deploying machine learning models and managing ML workflows in production
• Solid understanding of software engineering principles including design patterns, version control, unit testing, and CI/CD
• Familiarity with object-oriented and functional programming practices
• Experience developing RESTful APIs and microservices
• Proven experience with cloud engineering on AWS, especially services like SageMaker, Glue, Lake Formation, and Athena
• Infrastructure as Code experience using CloudFormation, Terraform, or AWS CDK
• Experience with graph technologies and knowledge graphs (e.g., Neo4j, Amazon Neptune) is a plus

Preferred Qualifications

• Prior experience working with machine learning operations (MLOps) or AI platform teams
• Knowledge of knowledge graph construction and semantic modeling
• Background in big data environments and real-time data processing frameworks

Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract